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<div class="header">
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<a href="#nested-classes">类</a> &#124;
<a href="#func-members">函数</a>  </div>
  <div class="headertitle">
<div class="title">centroid.h 文件参考<div class="ingroups"><a class="el" href="group__common.html">Common components</a></div></div>  </div>
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<div class="contents">
<div class="textblock"><code>#include &lt;pcl/point_cloud.h&gt;</code><br />
<code>#include &lt;pcl/point_traits.h&gt;</code><br />
<code>#include &lt;pcl/PointIndices.h&gt;</code><br />
<code>#include &lt;pcl/cloud_iterator.h&gt;</code><br />
<code>#include &lt;pcl/common/impl/accumulators.hpp&gt;</code><br />
<code>#include &lt;pcl/common/impl/centroid.hpp&gt;</code><br />
</div>
<p><a href="centroid_8h_source.html">浏览源代码.</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
类</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structpcl_1_1_nd_centroid_functor.html">pcl::NdCentroidFunctor&lt; PointT, Scalar &gt;</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Helper functor structure for n-D centroid estimation.  <a href="structpcl_1_1_nd_centroid_functor.html#details">更多...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_centroid_point.html">pcl::CentroidPoint&lt; PointT &gt;</a></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
函数</h2></td></tr>
<tr class="memitem:gaf5729fae15603888b49743b118025290"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gaf5729fae15603888b49743b118025290"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:gaf5729fae15603888b49743b118025290"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.  <a href="group__common.html#gaf5729fae15603888b49743b118025290">更多...</a><br /></td></tr>
<tr class="separator:gaf5729fae15603888b49743b118025290"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac050f06179c72e8bc2665faf7f42a0aa"><td class="memTemplParams" colspan="2"><a id="ac050f06179c72e8bc2665faf7f42a0aa"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ac050f06179c72e8bc2665faf7f42a0aa"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, Eigen::Vector4f &amp;centroid)</td></tr>
<tr class="separator:ac050f06179c72e8bc2665faf7f42a0aa"><td class="memSeparator" colspan="2">&#160;</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:afda9ffdc3a6bb85098aa16e61d668682"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, Eigen::Vector4d &amp;centroid)</td></tr>
<tr class="separator:afda9ffdc3a6bb85098aa16e61d668682"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga26f5d53ac5362b04a5c8ed68c4c39038"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga26f5d53ac5362b04a5c8ed68c4c39038"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga26f5d53ac5362b04a5c8ed68c4c39038">pcl::compute3DCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:ga26f5d53ac5362b04a5c8ed68c4c39038"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.  <a href="group__common.html#ga26f5d53ac5362b04a5c8ed68c4c39038">更多...</a><br /></td></tr>
<tr class="separator:ga26f5d53ac5362b04a5c8ed68c4c39038"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a23daec3829d2d4100a2f185372b3753a"><td class="memTemplParams" colspan="2"><a id="a23daec3829d2d4100a2f185372b3753a"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a23daec3829d2d4100a2f185372b3753a"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Vector4f &amp;centroid)</td></tr>
<tr class="separator:a23daec3829d2d4100a2f185372b3753a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a81f00705f1116eb69a984286e1e1d2b9"><td class="memTemplParams" colspan="2"><a id="a81f00705f1116eb69a984286e1e1d2b9"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a81f00705f1116eb69a984286e1e1d2b9"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Vector4d &amp;centroid)</td></tr>
<tr class="separator:a81f00705f1116eb69a984286e1e1d2b9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gaef1048c26d7ee3cad4ae9436d1f4a5d6"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gaef1048c26d7ee3cad4ae9436d1f4a5d6"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gaef1048c26d7ee3cad4ae9436d1f4a5d6">pcl::compute3DCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:gaef1048c26d7ee3cad4ae9436d1f4a5d6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector.  <a href="group__common.html#gaef1048c26d7ee3cad4ae9436d1f4a5d6">更多...</a><br /></td></tr>
<tr class="separator:gaef1048c26d7ee3cad4ae9436d1f4a5d6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a31742212c6899b454c00d1efa2c31c70"><td class="memTemplParams" colspan="2"><a id="a31742212c6899b454c00d1efa2c31c70"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a31742212c6899b454c00d1efa2c31c70"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Vector4f &amp;centroid)</td></tr>
<tr class="separator:a31742212c6899b454c00d1efa2c31c70"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af59437e1008bc26ecc5399c390448d64"><td class="memTemplParams" colspan="2"><a id="af59437e1008bc26ecc5399c390448d64"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:af59437e1008bc26ecc5399c390448d64"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Vector4d &amp;centroid)</td></tr>
<tr class="separator:af59437e1008bc26ecc5399c390448d64"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga057c72764dfcd1276f7fe19bbfb380a7"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga057c72764dfcd1276f7fe19bbfb380a7"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga057c72764dfcd1276f7fe19bbfb380a7">pcl::compute3DCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:ga057c72764dfcd1276f7fe19bbfb380a7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector.  <a href="group__common.html#ga057c72764dfcd1276f7fe19bbfb380a7">更多...</a><br /></td></tr>
<tr class="separator:ga057c72764dfcd1276f7fe19bbfb380a7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af4605825a1d7113456c905716c518e73"><td class="memTemplParams" colspan="2"><a id="af4605825a1d7113456c905716c518e73"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:af4605825a1d7113456c905716c518e73"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Vector4f &amp;centroid)</td></tr>
<tr class="separator:af4605825a1d7113456c905716c518e73"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a202572bfcc54d5262fb2ab3a695d7682"><td class="memTemplParams" colspan="2"><a id="a202572bfcc54d5262fb2ab3a695d7682"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a202572bfcc54d5262fb2ab3a695d7682"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::compute3DCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Vector4d &amp;centroid)</td></tr>
<tr class="separator:a202572bfcc54d5262fb2ab3a695d7682"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gac36b146ec26b1ceb7be43a9ecaa010c4"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gac36b146ec26b1ceb7be43a9ecaa010c4"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">pcl::computeCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:gac36b146ec26b1ceb7be43a9ecaa010c4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3x3 covariance matrix of a given set of points. The result is returned as a Eigen::Matrix3f. Note: the covariance matrix is not normalized with the number of points. For a normalized covariance, please use computeNormalizedCovarianceMatrix.  <a href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">更多...</a><br /></td></tr>
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<tr class="memitem:a9a519f0128baede6be874e0947ad8147"><td class="memTemplParams" colspan="2"><a id="a9a519f0128baede6be874e0947ad8147"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a9a519f0128baede6be874e0947ad8147"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const Eigen::Vector4f &amp;centroid, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
<tr class="separator:a9a519f0128baede6be874e0947ad8147"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8b4e482f26037bee30f64693f33fa98e"><td class="memTemplParams" colspan="2"><a id="a8b4e482f26037bee30f64693f33fa98e"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a8b4e482f26037bee30f64693f33fa98e"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const Eigen::Vector4d &amp;centroid, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
<tr class="separator:a8b4e482f26037bee30f64693f33fa98e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gab5ea605f439a80daf6348547379bad8e"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gab5ea605f439a80daf6348547379bad8e"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">pcl::computeCovarianceMatrixNormalized</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:gab5ea605f439a80daf6348547379bad8e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute normalized the 3x3 covariance matrix of a given set of points. The result is returned as a Eigen::Matrix3f. Normalized means that every entry has been divided by the number of points in the point cloud. For small number of points, or if you want explicitely the sample-variance, use computeCovarianceMatrix and scale the covariance matrix with 1 / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by the computeCovarianceMatrix function.  <a href="group__common.html#gab5ea605f439a80daf6348547379bad8e">更多...</a><br /></td></tr>
<tr class="separator:gab5ea605f439a80daf6348547379bad8e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7c34bc132bc8d638839f1ca4e8ddea0f"><td class="memTemplParams" colspan="2"><a id="a7c34bc132bc8d638839f1ca4e8ddea0f"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a7c34bc132bc8d638839f1ca4e8ddea0f"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrixNormalized</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const Eigen::Vector4f &amp;centroid, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a5cf7877e22ed85622d8eea00880f7d35"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrixNormalized</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const Eigen::Vector4d &amp;centroid, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
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<tr class="memitem:ga73df83248bb8d4e74347822811be9359"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga73df83248bb8d4e74347822811be9359"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga73df83248bb8d4e74347822811be9359">pcl::computeCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:ga73df83248bb8d4e74347822811be9359"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3x3 covariance matrix of a given set of points using their indices. The result is returned as a Eigen::Matrix3f. Note: the covariance matrix is not normalized with the number of points. For a normalized covariance, please use computeNormalizedCovarianceMatrix.  <a href="group__common.html#ga73df83248bb8d4e74347822811be9359">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a6f49707c744252f4685a00772ec2c131"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4f &amp;centroid, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ac344ea8f7c57ec1759f1438d27c96ce0"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4d &amp;centroid, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
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<tr class="memitem:ga35305b1593d5417be615e940383f4ced"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga35305b1593d5417be615e940383f4ced"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga35305b1593d5417be615e940383f4ced">pcl::computeCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:ga35305b1593d5417be615e940383f4ced"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the 3x3 covariance matrix of a given set of points using their indices. The result is returned as a Eigen::Matrix3f. Note: the covariance matrix is not normalized with the number of points. For a normalized covariance, please use computeNormalizedCovarianceMatrix.  <a href="group__common.html#ga35305b1593d5417be615e940383f4ced">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a327ececf41f1808237b5d7ef6f96494e"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4f &amp;centroid, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a74070eb55600644b3f8de2d4d8d08bd2"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4d &amp;centroid, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
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<tr class="memitem:gad8f6fde995ab21ab95267c22c7b12c90"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gad8f6fde995ab21ab95267c22c7b12c90"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gad8f6fde995ab21ab95267c22c7b12c90">pcl::computeCovarianceMatrixNormalized</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:gad8f6fde995ab21ab95267c22c7b12c90"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix of a given set of points using their indices. The result is returned as a Eigen::Matrix3f. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, use computeCovarianceMatrix and scale the covariance matrix with 1 / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by the computeCovarianceMatrix function.  <a href="group__common.html#gad8f6fde995ab21ab95267c22c7b12c90">更多...</a><br /></td></tr>
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<tr class="memitem:ab5801de93dff3974045a92317d6c8b46"><td class="memTemplParams" colspan="2"><a id="ab5801de93dff3974045a92317d6c8b46"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ab5801de93dff3974045a92317d6c8b46"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrixNormalized</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4f &amp;centroid, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ad8dfbb2960ae63831107379b1d72f0e3"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrixNormalized</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4d &amp;centroid, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
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<tr class="memitem:gadfb4158efe784f3d3a765f0747b13a80"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gadfb4158efe784f3d3a765f0747b13a80"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gadfb4158efe784f3d3a765f0747b13a80">pcl::computeCovarianceMatrixNormalized</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:gadfb4158efe784f3d3a765f0747b13a80"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix of a given set of points using their indices. The result is returned as a Eigen::Matrix3f. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, use computeCovarianceMatrix and scale the covariance matrix with 1 / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by the computeCovarianceMatrix function.  <a href="group__common.html#gadfb4158efe784f3d3a765f0747b13a80">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a8883fe1fb7c5c9de850f6520b68509f8"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrixNormalized</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4f &amp;centroid, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a5fe0230defb5a7854e0234234c21506b"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrixNormalized</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4d &amp;centroid, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
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<tr class="memitem:ga72dfb6e965df9752c88790e026a8ab5f"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga72dfb6e965df9752c88790e026a8ab5f"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">pcl::computeMeanAndCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:ga72dfb6e965df9752c88790e026a8ab5f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, scale the covariance matrix with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.  <a href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">更多...</a><br /></td></tr>
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<tr class="memitem:a8cc2ea3fcf34548958ee0d7e691fd150"><td class="memTemplParams" colspan="2"><a id="a8cc2ea3fcf34548958ee0d7e691fd150"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a8cc2ea3fcf34548958ee0d7e691fd150"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeMeanAndCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix3f &amp;covariance_matrix, Eigen::Vector4f &amp;centroid)</td></tr>
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<tr class="memitem:a21277bc4c42f68a98091745b9fd8232f"><td class="memTemplParams" colspan="2"><a id="a21277bc4c42f68a98091745b9fd8232f"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a21277bc4c42f68a98091745b9fd8232f"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeMeanAndCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix3d &amp;covariance_matrix, Eigen::Vector4d &amp;centroid)</td></tr>
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<tr class="memitem:gad2138293b6dd302ceaa128fae950f27d"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gad2138293b6dd302ceaa128fae950f27d"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gad2138293b6dd302ceaa128fae950f27d">pcl::computeMeanAndCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:gad2138293b6dd302ceaa128fae950f27d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, scale the covariance matrix with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.  <a href="group__common.html#gad2138293b6dd302ceaa128fae950f27d">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a16257de87265a9888fadd352245dee69"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeMeanAndCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix3f &amp;covariance_matrix, Eigen::Vector4f &amp;centroid)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:aaaac140ac40081942257bdc2a022a90b"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeMeanAndCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix3d &amp;covariance_matrix, Eigen::Vector4d &amp;centroid)</td></tr>
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<tr class="memitem:gac4d7bf1a81f21fb97505c91957b7f033"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gac4d7bf1a81f21fb97505c91957b7f033"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gac4d7bf1a81f21fb97505c91957b7f033">pcl::computeMeanAndCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:gac4d7bf1a81f21fb97505c91957b7f033"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, scale the covariance matrix with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.  <a href="group__common.html#gac4d7bf1a81f21fb97505c91957b7f033">更多...</a><br /></td></tr>
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<tr class="memitem:ac84951a6b448e68f38b93db5d657c833"><td class="memTemplParams" colspan="2"><a id="ac84951a6b448e68f38b93db5d657c833"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ac84951a6b448e68f38b93db5d657c833"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeMeanAndCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix3f &amp;covariance_matrix, Eigen::Vector4f &amp;centroid)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:aeff94982be65cb242843ce845a9fa1be"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeMeanAndCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix3d &amp;covariance_matrix, Eigen::Vector4d &amp;centroid)</td></tr>
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<tr class="memitem:ga5956698bec9ece7a491ad2fbbfbe6bc1"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga5956698bec9ece7a491ad2fbbfbe6bc1"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga5956698bec9ece7a491ad2fbbfbe6bc1">pcl::computeCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:ga5956698bec9ece7a491ad2fbbfbe6bc1"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, scale the covariance matrix with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.  <a href="group__common.html#ga5956698bec9ece7a491ad2fbbfbe6bc1">更多...</a><br /></td></tr>
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<tr class="memitem:a1792af32d68f02d0ae84aea7c25cf6d3"><td class="memTemplParams" colspan="2"><a id="a1792af32d68f02d0ae84aea7c25cf6d3"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a1792af32d68f02d0ae84aea7c25cf6d3"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a8cc2952e9da0204aed64bb967886240c"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
<tr class="separator:a8cc2952e9da0204aed64bb967886240c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gac33176152049aa1f63867afae8225000"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gac33176152049aa1f63867afae8225000"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gac33176152049aa1f63867afae8225000">pcl::computeCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:gac33176152049aa1f63867afae8225000"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, scale the covariance matrix with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.  <a href="group__common.html#gac33176152049aa1f63867afae8225000">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a505ea26dcb77a2f3c8db0a35e89f8ab5"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:adfef4a33858777dc188ca0350807c7ae"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
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<tr class="memitem:gacf3ff94b2145fb22871e41e87ee495b2"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gacf3ff94b2145fb22871e41e87ee495b2"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gacf3ff94b2145fb22871e41e87ee495b2">pcl::computeCovarianceMatrix</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</td></tr>
<tr class="memdesc:gacf3ff94b2145fb22871e41e87ee495b2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. Normalized means that every entry has been divided by the number of entries in indices. For small number of points, or if you want explicitely the sample-variance, scale the covariance matrix with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.  <a href="group__common.html#gacf3ff94b2145fb22871e41e87ee495b2">更多...</a><br /></td></tr>
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<tr class="memitem:a63b7fbcd5a7bf264c08d5b7b534d34fe"><td class="memTemplParams" colspan="2"><a id="a63b7fbcd5a7bf264c08d5b7b534d34fe"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a63b7fbcd5a7bf264c08d5b7b534d34fe"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix3f &amp;covariance_matrix)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ad570c977482c84dc1fd2ec82ff664bc5"><td class="memTemplItemLeft" align="right" valign="top">unsigned int&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeCovarianceMatrix</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix3d &amp;covariance_matrix)</td></tr>
<tr class="separator:ad570c977482c84dc1fd2ec82ff664bc5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga7f82fbd4e17063ab86287a2543bdea88"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga7f82fbd4e17063ab86287a2543bdea88"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">pcl::demeanPointCloud</a> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out, int npts=0)</td></tr>
<tr class="memdesc:ga7f82fbd4e17063ab86287a2543bdea88"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation  <a href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a0212a746948007708bcfaa4117ea7461"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Vector4f &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out, int npts=0)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a71766012ea8618588baa1dc073dac1b4"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Vector4d &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out, int npts=0)</td></tr>
<tr class="separator:a71766012ea8618588baa1dc073dac1b4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga7953d5001218e840a3a10a2c8649461e"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga7953d5001218e840a3a10a2c8649461e"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga7953d5001218e840a3a10a2c8649461e">pcl::demeanPointCloud</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="memdesc:ga7953d5001218e840a3a10a2c8649461e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation  <a href="group__common.html#ga7953d5001218e840a3a10a2c8649461e">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ae1ca17f3decd37c512d958afa4d88ce0"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Vector4f &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
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<tr class="memitem:a6afc80fd70f4436ccce44de9241a1ba3"><td class="memTemplParams" colspan="2"><a id="a6afc80fd70f4436ccce44de9241a1ba3"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a6afc80fd70f4436ccce44de9241a1ba3"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Vector4d &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="separator:a6afc80fd70f4436ccce44de9241a1ba3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gab6c182905d630aa151bac567011b93d5"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gab6c182905d630aa151bac567011b93d5"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gab6c182905d630aa151bac567011b93d5">pcl::demeanPointCloud</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="memdesc:gab6c182905d630aa151bac567011b93d5"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation  <a href="group__common.html#gab6c182905d630aa151bac567011b93d5">更多...</a><br /></td></tr>
<tr class="separator:gab6c182905d630aa151bac567011b93d5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa23f4841f8ce0b0dcbe448cd29435f68"><td class="memTemplParams" colspan="2"><a id="aa23f4841f8ce0b0dcbe448cd29435f68"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:aa23f4841f8ce0b0dcbe448cd29435f68"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4f &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a0fd3d64f5633ec1fc50bbec65017d161"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4d &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="separator:a0fd3d64f5633ec1fc50bbec65017d161"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga516ff833c2593ba6e53d369b25989f81"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga516ff833c2593ba6e53d369b25989f81"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga516ff833c2593ba6e53d369b25989f81">pcl::demeanPointCloud</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="memdesc:ga516ff833c2593ba6e53d369b25989f81"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation  <a href="group__common.html#ga516ff833c2593ba6e53d369b25989f81">更多...</a><br /></td></tr>
<tr class="separator:ga516ff833c2593ba6e53d369b25989f81"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1b9d4b8b8ac294c8273318b7af44b477"><td class="memTemplParams" colspan="2"><a id="a1b9d4b8b8ac294c8273318b7af44b477"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a1b9d4b8b8ac294c8273318b7af44b477"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4f &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="separator:a1b9d4b8b8ac294c8273318b7af44b477"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a989ce2a2f9a6f14cbfefee1a3eaa40e6"><td class="memTemplParams" colspan="2"><a id="a989ce2a2f9a6f14cbfefee1a3eaa40e6"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a989ce2a2f9a6f14cbfefee1a3eaa40e6"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4d &amp;centroid, <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_out)</td></tr>
<tr class="separator:a989ce2a2f9a6f14cbfefee1a3eaa40e6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga553c2ce698f074fe38d74f01b57a3343"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga553c2ce698f074fe38d74f01b57a3343"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga553c2ce698f074fe38d74f01b57a3343">pcl::demeanPointCloud</a> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, Eigen::Dynamic &gt; &amp;cloud_out, int npts=0)</td></tr>
<tr class="memdesc:ga553c2ce698f074fe38d74f01b57a3343"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix  <a href="group__common.html#ga553c2ce698f074fe38d74f01b57a3343">更多...</a><br /></td></tr>
<tr class="separator:ga553c2ce698f074fe38d74f01b57a3343"><td class="memSeparator" colspan="2">&#160;</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ae5a74008d2df6abde28a843a243ef011"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Vector4f &amp;centroid, Eigen::MatrixXf &amp;cloud_out, int npts=0)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a3a54767789c47edda970ae0cc04aee33"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (ConstCloudIterator&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_iterator, const Eigen::Vector4d &amp;centroid, Eigen::MatrixXd &amp;cloud_out, int npts=0)</td></tr>
<tr class="separator:a3a54767789c47edda970ae0cc04aee33"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gae19c71709093628e61037337056b99fa"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gae19c71709093628e61037337056b99fa"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gae19c71709093628e61037337056b99fa">pcl::demeanPointCloud</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, Eigen::Dynamic &gt; &amp;cloud_out)</td></tr>
<tr class="memdesc:gae19c71709093628e61037337056b99fa"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix  <a href="group__common.html#gae19c71709093628e61037337056b99fa">更多...</a><br /></td></tr>
<tr class="separator:gae19c71709093628e61037337056b99fa"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8dfb2a1c7a8437bac36540227bc55888"><td class="memTemplParams" colspan="2"><a id="a8dfb2a1c7a8437bac36540227bc55888"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a8dfb2a1c7a8437bac36540227bc55888"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const Eigen::Vector4f &amp;centroid, Eigen::MatrixXf &amp;cloud_out)</td></tr>
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<tr class="memitem:a9820d1ad515c00d37ef4c7594b27d1ab"><td class="memTemplParams" colspan="2"><a id="a9820d1ad515c00d37ef4c7594b27d1ab"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a9820d1ad515c00d37ef4c7594b27d1ab"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const Eigen::Vector4d &amp;centroid, Eigen::MatrixXd &amp;cloud_out)</td></tr>
<tr class="separator:a9820d1ad515c00d37ef4c7594b27d1ab"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga79129774e295b6a11559bed8dc5f0b48"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga79129774e295b6a11559bed8dc5f0b48"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga79129774e295b6a11559bed8dc5f0b48">pcl::demeanPointCloud</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, Eigen::Dynamic &gt; &amp;cloud_out)</td></tr>
<tr class="memdesc:ga79129774e295b6a11559bed8dc5f0b48"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix  <a href="group__common.html#ga79129774e295b6a11559bed8dc5f0b48">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a378ab3561cb3ec8705efab18dd903acf"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4f &amp;centroid, Eigen::MatrixXf &amp;cloud_out)</td></tr>
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<tr class="memitem:a60b9a398a5ca5cdffe97974c40791159"><td class="memTemplParams" colspan="2"><a id="a60b9a398a5ca5cdffe97974c40791159"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a60b9a398a5ca5cdffe97974c40791159"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const std::vector&lt; int &gt; &amp;indices, const Eigen::Vector4d &amp;centroid, Eigen::MatrixXd &amp;cloud_out)</td></tr>
<tr class="separator:a60b9a398a5ca5cdffe97974c40791159"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga539a53e4b17ad9ed2f00ae8b2e464221"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga539a53e4b17ad9ed2f00ae8b2e464221"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga539a53e4b17ad9ed2f00ae8b2e464221">pcl::demeanPointCloud</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, Eigen::Dynamic &gt; &amp;cloud_out)</td></tr>
<tr class="memdesc:ga539a53e4b17ad9ed2f00ae8b2e464221"><td class="mdescLeft">&#160;</td><td class="mdescRight">Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix  <a href="group__common.html#ga539a53e4b17ad9ed2f00ae8b2e464221">更多...</a><br /></td></tr>
<tr class="separator:ga539a53e4b17ad9ed2f00ae8b2e464221"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9f7d5505eb5192ddae706e461dc91c8b"><td class="memTemplParams" colspan="2"><a id="a9f7d5505eb5192ddae706e461dc91c8b"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a9f7d5505eb5192ddae706e461dc91c8b"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4f &amp;centroid, Eigen::MatrixXf &amp;cloud_out)</td></tr>
<tr class="separator:a9f7d5505eb5192ddae706e461dc91c8b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a593f079cc31336760d9e5b8a9b3ec5e4"><td class="memTemplParams" colspan="2"><a id="a593f079cc31336760d9e5b8a9b3ec5e4"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a593f079cc31336760d9e5b8a9b3ec5e4"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::demeanPointCloud</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud_in, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, const Eigen::Vector4d &amp;centroid, Eigen::MatrixXd &amp;cloud_out)</td></tr>
<tr class="separator:a593f079cc31336760d9e5b8a9b3ec5e4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga4d047d6f7b50a2d81306cc59ac927179"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga4d047d6f7b50a2d81306cc59ac927179"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga4d047d6f7b50a2d81306cc59ac927179">pcl::computeNDCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:ga4d047d6f7b50a2d81306cc59ac927179"><td class="mdescLeft">&#160;</td><td class="mdescRight">General, all purpose nD centroid estimation for a set of points using their indices.  <a href="group__common.html#ga4d047d6f7b50a2d81306cc59ac927179">更多...</a><br /></td></tr>
<tr class="separator:ga4d047d6f7b50a2d81306cc59ac927179"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab12a9c691a9dad8617f06110dcdf337c"><td class="memTemplParams" colspan="2"><a id="ab12a9c691a9dad8617f06110dcdf337c"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ab12a9c691a9dad8617f06110dcdf337c"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeNDCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::VectorXf &amp;centroid)</td></tr>
<tr class="separator:ab12a9c691a9dad8617f06110dcdf337c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a49b8336923506cbc45f1b848abfffce8"><td class="memTemplParams" colspan="2"><a id="a49b8336923506cbc45f1b848abfffce8"></a>
template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a49b8336923506cbc45f1b848abfffce8"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeNDCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, Eigen::VectorXd &amp;centroid)</td></tr>
<tr class="separator:a49b8336923506cbc45f1b848abfffce8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:gaf936744f1fa429ebc22c2544e0d0a747"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:gaf936744f1fa429ebc22c2544e0d0a747"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#gaf936744f1fa429ebc22c2544e0d0a747">pcl::computeNDCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:gaf936744f1fa429ebc22c2544e0d0a747"><td class="mdescLeft">&#160;</td><td class="mdescRight">General, all purpose nD centroid estimation for a set of points using their indices.  <a href="group__common.html#gaf936744f1fa429ebc22c2544e0d0a747">更多...</a><br /></td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:aa682a13c6eb323c13a249b91015fc9d8"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeNDCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::VectorXf &amp;centroid)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:af71f5e22a2404a429fad507ef86e635c"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeNDCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, Eigen::VectorXd &amp;centroid)</td></tr>
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<tr class="memitem:ga9654681b5a78f1e3ad5566de05e1d638"><td class="memTemplParams" colspan="2">template&lt;typename PointT , typename Scalar &gt; </td></tr>
<tr class="memitem:ga9654681b5a78f1e3ad5566de05e1d638"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga9654681b5a78f1e3ad5566de05e1d638">pcl::computeNDCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::Matrix&lt; Scalar, Eigen::Dynamic, 1 &gt; &amp;centroid)</td></tr>
<tr class="memdesc:ga9654681b5a78f1e3ad5566de05e1d638"><td class="mdescLeft">&#160;</td><td class="mdescRight">General, all purpose nD centroid estimation for a set of points using their indices.  <a href="group__common.html#ga9654681b5a78f1e3ad5566de05e1d638">更多...</a><br /></td></tr>
<tr class="separator:ga9654681b5a78f1e3ad5566de05e1d638"><td class="memSeparator" colspan="2">&#160;</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:a7fdac43d0a93611d8e8a6759942d31c1"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeNDCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::VectorXf &amp;centroid)</td></tr>
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template&lt;typename PointT &gt; </td></tr>
<tr class="memitem:ad5cd43a281c8a8e8a21ce454604bb13a"><td class="memTemplItemLeft" align="right" valign="top">void&#160;</td><td class="memTemplItemRight" valign="bottom"><b>pcl::computeNDCentroid</b> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt; &amp;cloud, const <a class="el" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &amp;indices, Eigen::VectorXd &amp;centroid)</td></tr>
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<tr class="memitem:ga65222f7a25f5de1aff9b07d2aea361b1"><td class="memTemplParams" colspan="2">template&lt;typename PointInT , typename PointOutT &gt; </td></tr>
<tr class="memitem:ga65222f7a25f5de1aff9b07d2aea361b1"><td class="memTemplItemLeft" align="right" valign="top">size_t&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga65222f7a25f5de1aff9b07d2aea361b1">pcl::computeCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt; &amp;cloud, PointOutT &amp;centroid)</td></tr>
<tr class="separator:ga65222f7a25f5de1aff9b07d2aea361b1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ga02e71a096abe1156be18c6322c0728c0"><td class="memTemplParams" colspan="2">template&lt;typename PointInT , typename PointOutT &gt; </td></tr>
<tr class="memitem:ga02e71a096abe1156be18c6322c0728c0"><td class="memTemplItemLeft" align="right" valign="top">size_t&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="group__common.html#ga02e71a096abe1156be18c6322c0728c0">pcl::computeCentroid</a> (const <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointInT &gt; &amp;cloud, const std::vector&lt; int &gt; &amp;indices, PointOutT &amp;centroid)</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><p>Define methods for centroid estimation and covariance matrix calculus </p>
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